Consumer heterogeneity and online vs. offline retail spatial competition

This paper develops a game-theoretic spatial model featuring consumer heterogeneity in online vs. offline retailers’ spatial competition. We find that consumers’ browse-and-switch behavior intensifies the competition because both offline and online retailers’ price and profit decline when the behavior occurs, but it is not necessarily a threat to offline retailers especially when the product relates more closely to experience. We consider six equilibrium scenarios for different combinations of consumer behaviors when considering a hybrid retailer. The analysis taking consumer heterogeneity into consideration shows that the hybrid retailer operating both online and offline is not always the winner. Particularly, the business opportunity for the offline retailer lies in consumers’ willingness to pay in store, and whether the retailer launches an online store depends on the type of products and services provided.     

Why is Price Dispersion Higher Online than Offline? The Impact of Retailer Type and Shopping Risk on Price Dispersion

When physically similar products, of similar quality, are offered by retailers both online and offline, we often observe that the dispersion in prices of these products online is greater than the price dispersion offline. This observation runs counter to early theories that suggested price dispersion online would be smaller than that offline due to the ease of search and information availability online. This paper investigates and provides an explanation for this puzzling phenomenon by examining the impact of two important drivers of price dispersion: retailer type and consumers’ shopping risk. Retailer type refers to whether a retailer is a pure offline, pure online, or dual channel retailer. Shopping risk is defined as the product of consumers’ perceived risk of shopping and the transaction uncertainty related to shopping at different types of retailers.A game-theoretic approach is adopted to model consumers’ price search and product purchase, as well as price competition within and across retailer types in online and offline markets. Equilibrium pricing strategies are derived for different retailer types competing for different consumer segments with different levels of perceived shopping risk. The impact of retailer type and shopping risk on online versus offline price dispersion are quantified, and conditions when price dispersion is greater online than offline are identified.Results indicate that price dispersion is greater online when the number of pure online retailers is sufficiently large and is increasing in the number of pure online retailers. In addition, a reduction in online shopping risk may actually increase online price dispersion. Results further suggest that even without any online sales, dual channel retailers should maintain their online presence for the purpose of information dissemination, which justifies the importance for pure offline retailer to incorporate webrooming strategies, where consumers can search for prices online but purchase offline.     

Forecast information and traditional retailer performance in a dual-channel competitive market

Independent firms in a dual-channel competitive market are expected to have their own information about the nature of the market. In this research, we develop a game-theoretic model to examine the value of forecast information about consumers' willingness to pay. The model is based on a simultaneously played Bertrand game. Our results indicate that the profits of online as well as traditional retailers always increase with forecast accuracy, and that forecast accuracy has a greater effect on the performance of the traditional retailer than on that of the online retailer. Our results also show that the difference in profit between that of the traditional retailer and the online retailer increases with forecast accuracy. In addition we find that forecast accuracy is much more valuable to the traditional retailer when there is an increasing volatility in the market, an increasing level of consumer valuation of the product, and an increasing intensity in market competition. Based on our results, we derive optimal market strategies and identify directions of future research.     

Buyer Power,Transport Cost and Welfare

Manufacturers produce substitute products and sell to consumers in a linear city through competing retail stores. A low cost store obtains large market share by selling at low prices. Assume that a big retailer may exert buyer power by demanding wholesale discounts from manufacturers. The model identifies exclusionary effects of buyer power against competing retailers. It is also found that certain level of buyer power of a discount retailer may maximize social welfare, while that of a regular price retailer may maximize total consumer surplus. Nevertheless, excessive buyer power hurts both consumers and society.     

Shopping in the omnichannel supply chain under price competition and product return

In recent years, omnichannel retailing has created value for prospective consumers. The rise of omnichannel retailing has changed consumers' buying habits, and manufacturers are facing stiff competition from retailers. To reduce this competition effect, manufacturers and retailers often work together to reduce showroom display costs. Despite this practice, there is little understanding of how omnichannel retailing impacts supply chain (SC) profit under competitive conditions. We investigate the test-in-store-and-buy-online (TSBO) retailing strategy and its impact on SC profit and price competition between manufacturers. The retailer sells products of both manufacturers through its website but displays products of only one manufacturer in the showroom, which bears the displaying cost. The retailer adopts a return policy for the other manufacturer. Stackelberg game was used to examine how members of the chain interact, and Nash equilibrium was used to find optimal strategies for players under decentralized and integrated channels. The results show that the TSBO strategy in retailing benefits all supply chain players under the integrated channel. A further interesting finding is that omnichannel SC profits are highest when retailers adopt a return policy. When two manufacturers compete and adopt different sales models, the manufacturer who uses the TSBO retail model reaps the most profit. Several other managerial insights are drawn from sensitivity analyses.     

Online and offline retailing: What we know and directions for future research

The fast-paced growth of e-commerce is rapidly changing consumers’ shopping habits and shaping the future of the retail industry. While online retailing has allowed companies to overcome geographic barriers to selling and helped them achieve operational efficiencies, offline retailers have struggled to compete with online retailers, and many retailers have chosen to operate both online and offline. This paper presents a review of the literature on the interaction between e-commerce and offline retailing, highlighting empirical findings and generalizable insights, and discussing their managerial implications. Our review includes studies published in more than 50 different academic journals spanning various disciplines from the inception of the internet to present. We organize our paper around three main research questions. First, what is the relationship between online and offline retail channels including competition and complementarity between online and offline sellers as well as online and offline channels of an omnichannel retailer? Under this question we also try to understand the impact of e-commerce on market structure and what factors impact the intensity of competition /complementarity. Second, what is the impact of e-commerce on consumer behavior? We specifically investigate how e-commerce has impacted consumer search, its implications for price dispersion, and user generated content. Third, how has e-commerce impacted retailers’ key managerial decisions? The key research questions under this heading include: (i) What is the impact of big data on retailing? (ii) What is the impact of digitization on retailer outcomes? (iii) What is the impact of e-commerce on sales concentration? (iv) What is the impact of e-commerce and platforms on pricing? And (v) How should retailers manage product returns across online and offline channels? Under each section, we also develop detailed recommendations for future research which we hope will inspire continued interest in this domain.     

Compete in Price or Service?—A Study of Personalized Pricing and Money Back Guarantees

Retailers use both pricing and service strategies to respond to intensified competition. Here we develop a duopoly model to investigate the impact of the increasingly popular personalized pricing strategy (PPS) and the widely used Money Back Guarantee (MBG) customer returns policy. We consider two retailers who differ in customer satisfaction rates. Each retailer chooses a pricing strategy, PPS or uniform pricing, and a product return strategy, MBG or ‘no returns.’ We show that both PPS and MBG are dominant strategies, but their impact on retailers’ prices and profits are different; while PPS intensifies price competition and may lead to a prisoner’s dilemma in which both retailers may lose profit, MBG mitigates price competition and may result in a Pareto improvement in both retailers’ profits. Both PPS and MBG increase the size of the overall market, but not the total duopoly profit. The total customer surplus and social welfare may increase under either strategy. In addition, we obtain some interesting observations as to how our results may change if the product quality/customer satisfaction rate is endogenously chosen in the duopoly. Some of our findings are in contrast to related results reported in the literature.     

Extending variety seeking to multi-sided platforms: Impact of new retailer listing

This study uses theories of variety seeking to examine how a new retailer listing on a multi-sided platform (MSP) affects consumer buying behavior. Using a unique dataset from an online MSP, we evaluate changes in purchase frequency with individual retailers after a new one is listed. Contrary to expectations, the results indicate that consumers increase their purchase frequency at existing retailers. Moreover, compared to consistency seekers, variety-seeking consumers show a higher positive effect as they buy even more. This result is observed for retailers in both competing and non-competing product categories. Finally, we discuss the theoretical contributions and implications for MSPs and retailers.     

Price-aware enhanced dynamic recommendation based on deep learning

Price is one of the essential elements influencing consumer purchase behavior. Like consumers’ preferences in products, their price preferences also dynamically change over time. However, dynamic price preferences haven’t been fully considered in existed recommendation studies. In this study, we propose a deep learning-based dynamic recommendation model by considering consumers’ dynamic preferences in both product and price. We specially design a review-and-rating-based sequence generator to select products whose prices the consumers are satisfied with to form the new purchase sequence. We also develop a multi-level attention mechanism in the transformer layer to explore the correlations between consumers’ price choices and to combine the price preferences with the product preferences. Experimental results show the proposed model outperforms the state-of-the-art models on some real-world datasets. Our findings can help retailers understand consumers’ price preferences and make informed decisions related to pricing, discounting, and bundle sales strategies.     

Whether to offer return-freight insurance or open a physical showroom: A strategic analysis of an online retailer’s decisions

Return-freight insurance (RI) and physical showroom (PS) can be a double-edged sword for retailers, as they can help consumers reduce product mismatch and information uncertainty but may lead to higher return rates and operating and construction costs. In this study, we examine four corresponding configurations regarding whether to provide RI (yes-R, no-N) and whether to open a PS (yes-S, no-N): NN, RN, NS, and RS. First, we find that offering RI or opening a PS does not necessarily expand market demand. Whether demand grows is closely related to the RI premium. When the RI premium is low, the RN strategy, which offers only RI, can expand the market, and the NS and RS strategies, where retailers open a PS, can shrink the market. In addition, retailers offering RI charge a higher sales price, while those opening a PS adopt a price reduction strategy. Second, the optimal strategy configuration for retailers depends on four factors: the RI premium, the proportion of consumers, the retailer’s cost of handling returns and the PS construction cost. Retailers consider opening a PS only when both the proportion of high-cost consumers and the PS construction cost are low. An interesting result is that when the RI premium is higher, offering RI still benefits the retailer. Third, we present an intuitive decision support matrix to help retailers recommend the optimal strategy configuration, using the RI premium as a proxy for the product online return rate and the proportion of high-cost consumers as a proxy for the degree of product standardization. Depending on whether products with high (low) return rates are highly personalized or standardized, retailers decide whether to use an NS (RS) or NN (RN) strategy.     

Consumer Product Redistribution

Abstract

Formats for product redistribution are emerging and evolving, creating alternative channel options for consumers' disposition of unwanted possessions. These retail formats operate in both informal (e.g., garage sales) and formal (online auctions) economies. As consumers participate in redistribution channels, some retailers are confronted with new competition and the potential for declining sales. This article expands on both recycling and disposition literature by examining consumer disposition behavior and the flow of used products through various redistribution channels. Strategies are offered to address consumer disposition behaviors as well as to assist retailers in combating traditional and non-traditional competition.     

The retailer's brand promotion strategy under competition: The impact of supply uncertainty

While retailers are committed to promoting product brands to increase sales quantity and brand visibility, retailers are exposed to supply uncertainty. Therefore, we explore the brand promotion strategies of retailers in a competitive model. We then investigate the decision model under three different brand strategies and explore the equilibrium outcomes of stakeholders under supply uncertainty. In addition, we analyze and discuss social welfare under different scenarios. The results show that when the promotion cost is high (i.e., the cost effect dominates the market expansion effect), neither retailer promotes the product brand. When the promotion cost is low (i.e., the market expansion effect dominates the cost effect), both retailers tend to promote the product brands. When the promotion cost and market expansion match each other, only one retailer promotes the product brand becomes the equilibrium strategy. It is worth noting that when both retailers promote the product brand, the retailer falls into a prisoner's dilemma. In addition, we find that the supply uncertainty level diminishes the cost affordability and the motivation of retailers to promote the product brands. Interestingly, the supply uncertainty level reduces the possibility of retailers being in a prisoner's dilemma. Besides, market expansion (supply uncertainty) contributes to improving (diminishing) social welfare.     

See How Much We’ve Sold Already! Effects of Displaying Sales and Stock Level Information on Consumers’ Online Product Choices

Many online retailers make sales and stock level information live available to customers on their websites and offline retailers also increasingly can display this information. Yet it is unclear how consumers perceive such information and how it influences consumer choice. High sales and low stock may both signal popularity and quality, which will stimulate further sales. We however argue that sales level is more diagnostic than stock level as a cue and hence the effect of sales level on consumer choice will be stronger than that of stock level. Also, when both cues are available, the effect of sales level is expected to dominate. In addition, brand familiarity is expected to moderate these effects. These hypotheses are tested in two scenario-based online experiments in which participants choose between competing products for which information about either sales levels, stock levels, or both sales and stock levels is displayed. Results support the hypotheses and also show that sales level is indeed a more diagnostic cue than stock level. Analyses further reveal how perceptions of the popularity and quality of a product mediate the effects of sales and stock levels on consumer choice. The findings imply that retailers can successfully use sales and stock level information to induce quality perceptions and influence consumer choices.     

Retailer Dominance and Quality Variation: Observations and a Theoretical Explanation

A number of consumer and business reports suggest that slightly lower quality (or feature) versions of products are being sold through dominant retailers, while higher quality versions continue to be sold through weaker retailers and, customers are uninformed about such subtle differences. We study two intriguing questions based on this phenomenon namely (1.) why are lower quality-lower priced versions sold primarily through dominant retailers and not the weaker retailers? (2.) Why do sometimes the weaker retailers not inform customers about these quality differences? Using a game theoretic model, we find that when quality is noncontractible an increase in retail dominance leads to a decrease in quality offered by the dominant retailer vis-à-vis the weaker retailer. However, we show that the weaker retailer does not have an incentive to advertise its higher quality if quality differences are not too high. This situation arises endogenously when the dominant retailer is not too powerful as compared to the weaker retailer or when retail differentiation is high. The motivation for this result is traced to the threat of increased competition in the event of such advertising.     

Bid-Elicitation Interfaces and Bidding Behavior in Retail Interactive Pricing

Advances in information technology have led to a substantial increase in the use of interactive pricing mechanisms, where buyers (i.e., consumers) and sellers (i.e., retailers) enter a formal computer-mediated price-negotiation process during which consumers submit bids for a specific product. This article examines how the interface used for bid elicitation affects bidding behavior and, ultimately, retailer profit. Our focus is on one key aspect of the bid-elicitation interface – how retailers require bidders to articulate their bids. Evidence from four experiments involving economically consequential bids demonstrates that the candidate bid amounts specified by the retailer have a strong influence on bidding behavior, and consequently also on retailer profit. In particular, the level of candidate bid amounts has a positive effect on actual bid amounts, whereas it has a negative impact on the likelihood that a consumer will actually submit a bid. Critically, we show that the former effect can more than offset the latter to cause an increase in retailer profit. We propose and find support for two distinct pathways driving this phenomenon – the candidate bid amounts (1) influence bidders’ valuations of the offered product and (2) shape bidders’ beliefs about what bid amounts will be successful. Our results highlight the importance of the design of user interfaces for interactive pricing, demonstrating that even seemingly innocuous aspects of interfaces can have a dramatic impact on bidding behavior and retailer profit.     

Bridge,Focus, Attack,or Stimulate: Retail Category Management Strategies with a Store Brand

We investigate a monopolist retailer's category management strategy where the main strategic decisions are how to horizontally position a store brand relative to the incumbent national brands and how to price the store and national brands for retail category profit maximization. We analyze a market composed of two consumer segments with differing tastes and heterogeneity with respect to willingness to pay and a product category consisting of two competing national brands and one store brand. We find that contrary to the existing literature, it is not always optimal for a retailer to position its store brand against the leading national brand; instead there are many situations where it is best to position the store brand close to the weaker national brand or to position it in the “middle” so it appeals to both national brands' target segments. In the process we identify four distinct category management strategies that a retailer can use with a store brand. In three of these the optimal store brand price is the brand's monopoly price, while in the remaining one strategy the price is lower. We also suggest an easy to implement means for a retailer to determine which strategy is best to use, depending on the particular competitive environment present before the introduction of the store brand and the relative quality of the store brand. We find that the store brand entry is most beneficial to the retailer when the national brands are moderately differentiated. Finally we show that introducing a store brand not only allows the retailer to garner a higher share of the channel profits through higher retail margins, but also often provides the retailer the benefit of increases in national brand unit sales as well as incremental sales from the store brand. JEL Classification: M310     

Consumer response to retailer use of cause-related marketing: Is more fit better?

Although marketers increasingly rely upon cause-related marketing strategies to increase sales, controversy exists regarding whether a retailer should partner with causes offering high or low fit levels with its core business practices. The present investigation extends prior research by examining how retailer–cause fit affects consumer evaluations of retailers’ cause-related marketing strategies. The results indicate that the effects of retailer–cause fit are moderated by consumer perceptions of the retailer's motive for engaging in cause-related marketing (Study 1), by the affinity that consumers hold for the social cause component of the campaign (Study 2), as well as by the interactive effects associated with the two moderators (Study 3).     

Refunds and collusion in service industries

This paper investigates industry-wide agreements on joint refund policies, and how they influence price competition. We compute the profit of fully-colluding, competing, and semicolluding service providers who offer refunds to those consumers who do not show up at the time of service. Our main findings are that both a monopoly serving all consumer types, and semicollusive service providers offer full refunds. In contrast, competing service providers offer only partial refunds. Finally, refund policies are investigated under moral hazard behavior.     

Online marketing: When to offer a refund for advanced sales

Advance selling is a marketing strategy commonly used by online retailers to increase sales by exploiting consumer valuation uncertainty. Recently, some online retailers have started to allow refunds on products sold in advance. On the one hand this reduces the net advance sales, but on the other hand it allows a higher advance sales price. This research is the first to explore the overall effect of allowing a refund on profits from advance sales, identifying conditions where advance selling with or without refunds (or no advance selling at all) is best. We analytically compare the profits of three advance selling strategies: none, without refund, and with refund. We show that selling in advance and allowing a refund is optimal for products with a relatively small profit margin and small strategic market size, and that the added profit can be considerable. Our results guide managers in selecting the right advance selling strategy. To facilitate this, we graphically display, based on the two dimensions of regular profit margin and strategic market size, under what conditions the different strategies are optimal.     

Retailer service acceptance: simply adding a service to the offer portfolio or committing to marketing it

By virtue of their significant influence on customers’ decisions, retailers’ acceptance of a service plays a significant role in the success of that service. Therefore, retailers’ acceptance of the service and commitment to selling the service must be ensured. However, this issue has attracted limited attention in acceptance research, which tends to focus on goods, technologies and consumers. Based on a survey of consumer durables retailers in three countries, this study focuses on retailer acceptance of a complimentary use-guarantee service, which is meant to maintain customer’s ability to use a semi-durable consumer product. The results of this study link retailers’ perceived usefulness, and commitment & effort to their service acceptance. Manufacturer support was found to moderate the relationship between ease of use and acceptance. Further, nationality, retailer’s own use of the service as a consumer and the importance of the manufacturer’s business for retailers were important for retailer acceptance. Thus, manufacturers need to focus as strongly on retailer acceptance as on the end customer acceptance to ensure service success. They also need to ensure the usefulness of the service for retailer, give retailers a reason to commit to the service sales and provide enough support to make retailers comfortable in selling the service.